Formation of Realistic Networks

人们明显缺乏对具有经验观察到的性质的大规模网络是如何形成的理解。我们通过设计和探索网络形成模型的框架来解决这个问题。我们的目标是通过分析和经验检验，网络创建模型的新方法如何能够成功地结合现实网络的几个普遍特征。这个方向的一个特别关注是理解网络创造模型的力量，这些模型源于博弈论假设和理性代理人的相互作用。此外，网络增强的顺序优化模型是一个原创性的、极未探索的方向。

There is an eminent lack of understanding of how large-scale networks with empirically observed properties are formed. We approach this problem by designing and exploring a framework of network formation models. Our goal is to analytically and empirically examine, how new approaches for network creation models can be successful in combining several of the prevalent features of realistic networks. A special focus in this direction is the understanding of the power of network creation models resulting from game- theoretic assumptions and the interplay of rational agents. Moreover, an original and vastly unexplored direction are sequential optimization models for network augmentation.